Altered source-based EEG coherence of resting-state sensorimotor network in early-stage Alzheimer's disease compared to mild cognitive impairment

Hsiao, Fu Jung; Chen, Wei Ta; Wang, Yuh Jen; Yan, Sui Hing; Lin, Yung Yang

doi:10.1016/j.neulet.2013.10.056

Cited by 24 publications

(19 citation statements)

References 38 publications

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“…And the global coherence of the MDD group is significantly higher than that of the healthy group in the theta band (4-8 Hz). In alpha (8-13 Hz) and beta bands (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), there is no diacritic difference in both groups.…”

Section: Global Coherencementioning

confidence: 99%

“…Prior EEG coherence based on discriminant function analysis (DFA) rules was used to explore possible neurophysiological differences between Asperger's Syndrome (ASP) and the Autism Spectrum Disorders (ASD) and successfully distinguished ASP and ASD populations [28]. Using EEG source-based coherence in Alzheimer's disease (AD) showed increased delta coherences between the bilateral precentral, left supplementary motor area (SMA), and right precentral [29].…”

Section: Complexitymentioning

confidence: 99%

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A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

Jing

et al. 2017

Complexity

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A large number of studies demonstrated that major depressive disorder (MDD) is characterized by the alterations in brain functional connections which is also identifiable during the brain's "resting-state." But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST) analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG) sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

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Section: Global Coherencementioning

confidence: 99%

Section: Complexitymentioning

confidence: 99%

A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

Jing

et al. 2017

Complexity

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“…In mild cognitive impairment (MCI), interaction between EEG-signals (today most often known as connectivity Aertsen and Preissl, 1991) was found to be a reliable marker for cerebral reserve capacity (Teipel et al, 2016), response to interventions (Klados et al, 2016), and to monitor and predict disease progression from MCI to Alzheimer's disease (Rossini et al, 2006; Giannakopoulos et al, 2009; Drago et al, 2011; Dai and He, 2014; Hsiao et al, 2014; Wurtman, 2015; Babiloni et al, 2016; Vecchio et al, 2016). …”

Section: Introductionmentioning

confidence: 99%

Reliability of EEG Interactions Differs between Measures and Is Specific for Neurological Diseases

Höller

Butz

Thomschewski

et al. 2017

Front. Hum. Neurosci.

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Alterations of interaction (connectivity) of the EEG reflect pathological processes in patients with neurologic disorders. Nevertheless, it is questionable whether these patterns are reliable over time in different measures of interaction and whether this reliability of the measures is the same across different patient populations. In order to address this topic we examined 22 patients with mild cognitive impairment, five patients with subjective cognitive complaints, six patients with right-lateralized temporal lobe epilepsy, seven patients with left lateralized temporal lobe epilepsy, and 20 healthy controls. We calculated 14 measures of interaction from two EEG-recordings separated by 2 weeks. In order to characterize test-retest reliability, we correlated these measures for each group and compared the correlations between measures and between groups. We found that both measures of interaction as well as groups differed from each other in terms of reliability. The strongest correlation coefficients were found for spectrum, coherence, and full frequency directed transfer function (average rho > 0.9). In the delta (2–4 Hz) range, reliability was lower for mild cognitive impairment compared to healthy controls and left lateralized temporal lobe epilepsy. In the beta (13–30 Hz), gamma (31–80 Hz), and high gamma (81–125 Hz) frequency ranges we found decreased reliability in subjective cognitive complaints compared to mild cognitive impairment. In the gamma and high gamma range we found increased reliability in left lateralized temporal lobe epilepsy patients compared to healthy controls. Our results emphasize the importance of documenting reliability of measures of interaction, which may vary considerably between measures, but also between patient populations. We suggest that studies claiming clinical usefulness of measures of interaction should provide information on the reliability of the results. In addition, differences between patient groups in reliability of interactions in the EEG indicate the potential of reliability to serve as a new biomarker for pathological memory decline as well as for epilepsy. While the brain concert of information flow is generally variable, high reliability, and thus, low variability may reflect abnormal firing patterns.

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“…The spectral power was derived from the averaged spectrum across the epochs. The spectral powers are defined as the mean values within the delta (1-4 Hz), theta (4-8 Hz), alpha (8)(9)(10)(11)(12)(13), beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25), and gamma (25-40 Hz) frequency bands. The spectral power was normalized by means of dividing the power of each frequency band by the total power from delta to gamma, which has been reported to adequately reduce the interindividual variability in previous EEG studies.…”

Section: Spectral Power Analysismentioning

confidence: 99%

Altered Resting-State Cortical EEG Oscillations in Patients With Severe Asymptomatic Carotid Stenosis

et al. 2014

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Asymptomatic carotid stenosis is characterized by altered cerebral hemodynamics and cognitive impairment, but the underlying neurophysiological mechanism remains unclear. To elucidate the alterations of cortical activities, resting-state electrophysiological activities were recorded from patients with mild (<30%; n=10; age 57-85 years), moderate (30% to 50%; n=11; age 66-88 years), and severe (>50%; n=8; age 67-91 years) carotid stenosis. The current density and oscillatory power of the cortical sources were analyzed using the minimum norm estimates method combined with fast Fourier transform analysis. Our results indicate that the cortical current density among regions of the brain was similar, irrespective of the degree of carotid stenosis. With regard to the cortical oscillations, augmented theta activities in the bilateral parietal, left temporal, and left occipital regions and attenuated alpha activities in the bilateral frontal and right central regions were obtained in patients with severe asymptomatic carotid stenosis. We suggest that the source-based cortical oscillations at theta and alpha bands might reflect the alterations of the brain activities and characterize the altered neurophysiological mechanism of the brain with at least 50% occlusion of the carotid artery. Further longitudinal studies with larger populations are warranted to verify the present findings.

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Altered source-based EEG coherence of resting-state sensorimotor network in early-stage Alzheimer's disease compared to mild cognitive impairment

Cited by 24 publications

References 38 publications

A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

Reliability of EEG Interactions Differs between Measures and Is Specific for Neurological Diseases

Altered Resting-State Cortical EEG Oscillations in Patients With Severe Asymptomatic Carotid Stenosis

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